Joint replacement surgery is a commonly performed procedure to relieve pain and restore the function of a patient's degenerated joint. The position, orientation and compliance of the prosthetics implanted into the joint are critical factors that have a significant effect on the clinical outcome of the patient. Therefore, computer assisted surgical devices are gaining popularity as a tool to pre-operatively plan and precisely execute the plan to ensure an accurate final position and orientation of the prosthetics within the patient's bone that can improve long term clinical outcomes and increase the survival rate of the prosthesis. In general, the computer assisted surgical systems include two components, an interactive pre-operative planning software program and a computer assisted surgical device that utilizes the pre-operative data from the software to assist the surgeon in precisely executing the procedure.
The conventional interactive pre-operative planning software generates a three dimensional (3-D) model of the patient's bony anatomy from a computed tomography (CT) or magnetic resonance imaging (MRI) image dataset of the patient. A set of 3-D computer aided design (CAD) models of the manufacturer's prosthesis are pre-loaded in the software that allows the user to place the components of a desired prosthesis to the 3-D model of the boney anatomy to designate the best fit, position and orientation of the prosthesis to the bone. The user can then save this pre-operative planning data to an electronic medium that is loaded and read by a surgical device to assist the surgeon intra-operatively in executing the plan.
In certain prior art systems, with reference to FIG. 1, a cutting strategy or set of instructions to create a cavity is pre-defined, validated and fixed for a given manufacturers prosthesis module 101. The fixed parameters for a prosthetic cutting strategy includes the cutter tool orientations, the cut paths, cut volume, cutting speed, and cutting orientations that are dependent on the size and dimensions of the prosthesis in the manufacturer's prosthesis module. A surgeon with the use of a planning workstation 102 and a 3-D model of the patient's bone positions and orients the appropriate prosthetic in the desired location 103. Intra-operatively, the data is transferred to a computer assisted surgical system 104 and the patient's bone is registered to the 3-D model and surgical system that indicates to the surgical device where to start cutting in relation to the bone to obtain the desired position and orientation of the prosthesis when implanted 105. Although the fixed parameters ensure reproducibility of the cut volume for a given prosthesis, these conventional systems limit the ability of a surgeon to plan for other clinical factors depending on other clinical needs. For example, the surgeon may want to adjust a fixed parameter as to protect or decrease the amount of bone removed in a certain anatomical location or to accommodate an unexpected bone density. Additionally, the surgeon may want to specify a different position and orientation of the cutting tool based on the surgeons surgical approach, the amount of surgical access, exposure of the surgical area that may be dependent on a patient's body mass index (BMI) or other clinical priorities.
Additionally, one of the main goals of computer assisted surgery is to define a patient specific plan and precisely execute the procedure, in a timely manner, on a patient. The accuracy of the cut volume for a given implant is critical and errors can accumulate based on registration error, cutter manufacturing tolerances and implant manufacturing tolerances. Registration techniques well known in the art such as point to surface registration can align the coordinate frames of a patient's bone to the coordinate frames of a 3-D model of a patient's bone and to the coordinate frame of the surgical device. The registration technique results in coordinate frames that are aligned within 1 mm; however that error is still propagated and affects the overall error of the system and the resulting cut-volume. Current safety strategies are used to stop cutting when the cutter encounters hard tissues that may indicate cutting outside of the prescribed cut volume by measuring the force on the end mill, however during milling of the softer tissue (trabecular bone) there are no monitoring techniques to ensure the accuracy of the cutting within the cut volume.
In addition to ensuring the accuracy of the system and optimizing the cut-paths with pre-operative CT values, the time required for a procedure can be reduced by using the estimated bone density to define a cutting speed and feed rate automatically in the pre-operative planning stage. Since the cutter speed and cutter engagement is dependent upon the density of the bone, these parameters can be defined for specific regions within the volume to be cut in the pre-operative planning software and those instructions transferred to the surgical device to be implemented intra-operatively. There have been processes proposed to use image intensities from pre-operative image data to estimate a patient's bone density to calculate optimized cutter speeds and feed rates to reduce operating times intra-operatively (see for example U.S. Patent Publication 20110306985 A1).
However, studies have shown that there can be significant variability between absolute CT values (Hounsfield units) between CT scanners and even different CT scanners from the same manufacturer (Sande, Erlend et al. Phys. Med. Biol. 55 (2010) 5123-5135). Therefore, the variability in CT values from different CT scanners can vary, even with the same CT scanning protocol. This variability will affect a corresponding cutting speed and feed rate on a case by case basis. Considering that different hospitals and practitioners will use the CT scanners that are available at their site, it makes it difficult to rely on the CT values from different scanners and accurately estimate a bone density of a patient. Additionally, different materials, designs and configurations of the components for a cutting system can change or vary between different systems that affect what materials and at what rates the cutting can be accomplished. For example, the cutter design, cutter stiffness, safety parameters, cutter size all affect the chip load, feed rate, and cutter speed for a given density of bone to be cut. As noted above, variations in CT values to estimate bone density must also be considered in planning a procedure.
Therefore, there exists a need to provide a process with a set of validated cutting strategies for a given implant module whereupon the process provides options that allow a user to adjust parameters to specify a cut path and cavity to receive a prosthetic. In this way, a user can accommodate clinical needs into the planned procedure. There is a further need to accurately calculate and/or monitor a patient's bone density to reduce the cutting time to create a cavity to receive a prosthetic for any cutting system and from any CT pre-operative imaging data. There further exists a need to use a more accurate assessment of bone density to produce a better bone interface with the prosthetic. There also exists a need to monitor the accuracy of a cut-path during cutting that can be accomplished by the surgical system. There also exists a need to improve the accuracy of the cut cavity due to variations in implant and cutter manufacturing tolerances.